Knowledge search system

ABSTRACT

A system and method to manage data associated with a merchant system to provide in response to a search query from an end user system. The system and method generate a custom entity type including one or more fields comprising first data corresponding to the merchant system. An update to the first data of the custom entity type can be received and an updated custom entity type is generated. The updated custom entity type is distributed to multiple business listing provider systems configured to provide search results associated with the merchant system in response to a search query from an end user system. The system and method can also generate a search experience interface including multiple input fields. The search experience interface is displayed to an end user to receive search terms via the first input and the second input field in response to a single search action.

CROSS REFERENCE TO RELATED APPLICATION

This application claims the benefit of U.S. Provisional Application No.62/749,457, filed Oct. 23, 2018, titled “Knowledge Search System”, theentire disclosure of which is incorporated herein by this reference.

TECHNICAL FIELD

The disclosure relates generally to a knowledge search platform, andmore particularly to a search platform having searchable elements thatare customizable by an entity.

BACKGROUND

Historically, an enormous amount of time, money, and effort has beenexpended by merchants (e.g., businesses and individuals) in order topublish information (e.g., advertisements) regarding their products andservices to consumers (e.g., end users) in an electronic environment.For generations, various media have been used to realize such businessmatters. The pervasive nature of open networks, such as the Internet,has provided a global means to attract new customers and retain oldcustomers.

The end users may use a search engine to obtain merchant-relatedinformation published and accessible via a network (e.g., the Internet).Search engines are software programs that search databases, and collectand display information related to search terms specified by an enduser. The merchant's interaction with the search engine is an importantfactor in the merchant's ability to reach end users and provide the endusers with quality information about the merchant that is responsive tothe end user's search query.

BRIEF DESCRIPTION OF THE FIGURES

The present disclosure will be understood more fully from the detaileddescription given below and from the accompanying drawings of variousimplementations of the disclosure.

FIG. 1 illustrates an example environment that includes a knowledgesearch system, according to embodiments of the present disclosure.

FIG. 2 is a flow diagram of an example method to generate search resultsin response to a search query from a developer system, according toembodiments of the present disclosure.

FIG. 3 illustrates a diagram including a knowledge search systemconfigured to execute a search algorithm and operatively couple to adeveloper user system and marketer user system, according to embodimentsof the present disclosure.

FIG. 4 illustrates an example interface generated by a knowledge searchsystem, according to embodiments of the present disclosure.

FIG. 5 is a diagram illustrating an example generation of a searchexperience type by knowledge search system, according to embodiments ofthe present disclosure.

FIGS. 6A-6E show example interfaces relating to management of searchexperiences by a knowledge search system, according to embodiments ofthe present disclosure.

FIGS. 7A-7B show example interfaces relating to management of analyticsby a knowledge search system, according to embodiments of the presentdisclosure.

FIG. 8 illustrates an example interface relating to search experienceconfiguration and analytics managed by a knowledge search system,according to embodiments of the present disclosure.

FIG. 9A illustrates a flow diagram of an example method to generate arelationship type associating multiple entity types to manage updates ina knowledge graph associated with a merchant system, according toembodiments of the present disclosure.

FIG. 9B-9C illustrate example interfaces relating to the generation ofentity types and relationship types, according to embodiments of thepresent disclosure.

FIG. 10 illustrates an example interface to the generation of fieldsrelating to a custom entity type generated by a knowledge search system,according to embodiments of the present disclosure.

FIG. 11 is a block diagram of an example computer system in whichimplementations of the present disclosure can operate.

DETAILED DESCRIPTION

To find relevant data with respect to a query received from an end user(e.g., a user initiating a search via a web interface), many searchengines use a keyword search based on text data provided by the enduser. In conducting the search, the end user seeks to identify a webelement (e.g., a webpage) that is responsive to the query that is copiedand indexed by a search engine based on the keywords in the search queryinput. If any of the keywords are incorrect (e.g., incomplete, include atypographical error, misspelled, etc.) or not indexed by the searchengine, the information the end user seeks may not be identified ordiscovered in response to the query. If the combination of keywords inthe search query matches a large number of webpages, information aboutthose webpages (e.g., links) may be listed on several search resultwebpages. This may require the end user to manually click on multiplelinks and sort through hundreds or thousands of similar webpages beforefinding the desired information. In other situations, the requestedinformation responsive to the user query may not be found due to a gap(e.g., a lack of content) between the keywords of the end user's queryand the online data associated with the entity (e.g., a merchant). Assuch, the amount of information and misinformation that the end usermust negotiate to find a particular product or service can produce anoverly time-consuming process that results in the end user abandoningthe search effort before obtaining the desired information, which canresult in a lost business opportunity for the merchant associated withthe search query.

Embodiments of the disclosure address the above-mentioned problems andother deficiencies with conventional search engine technologies byproviding a knowledge search system that enables end users (e.g., anindividual using a search engine to obtain knowledge or informationabout a merchant, product, or service) to employ one or more knowledgesearch features to generate an improved searching experience. In anembodiment, knowledge can be defined as “facts”, information, or dataregarding a subject that can be stored in a data store (e.g., adatabase) and queried to produce a responsive search result. In someembodiments, the knowledge search engine platform includes a naturallanguage processor that can process search query hints and autocompletion techniques to intuitively guide the end user toward a helpfulresponse. The knowledge search processing is conducted by the knowledgesearch engine platform based on information about certain dataassociated with the business product data.

In an embodiment, a merchant user (i.e., a user operating on behalf of abusiness entity; also referred to as an “entity user”) can use theknowledge search system of the present disclosure to manage andcentralize structured data relating to the entity (e.g., a company), andsurface the entity data on an electronic platform (e.g., a first-partywebsite associated with the entity or a third-party website). In anembodiment, the entity data can be provided via the knowledge searchsystem to multiple different publisher systems (e.g., websites, socialmedia platforms, search engine platforms, etc., such as Google™,Facebook™, Bing™, Apple™, etc.).

In an embodiment, the knowledge search system of the present disclosurecan utilize multiple different entity types (e.g., categories orclassifiers of information) to organize the searchable information togenerate a search result including the desired information in responseto a query. The different entity types can be a system-based entity type(e.g., a default entity type generated by the knowledge search systemand used by multiple different entities; also referred to as a “systementity type”) and a customized entity type (e.g., an entity typegenerated by the knowledge search system in accordance with instructionsfrom a particular entity). In an embodiment, the customized entity types(also referred to as “custom entity types”) can be generated, selected,and managed by an entity to provide a searchable informational elementfor us in generating search results in response to an end user search.

In an embodiment, a custom entity type can be mapped, linked, associatedwith, or logically connected to another entity type via a relationshiptype. In an embodiment, a relationship type can include a definedassociation between multiple entity types. For example, multiple customentity types can be associated by one or more relationship types. Inanother example, a custom entity type and a system entity type can belinked by one or more relationships types. Advantageously, thecustomized entity types and relationship types enable an entity user toupdate entity data via the knowledge search system (e.g., at a single“location” or via a system) and have the entity data updated on andacross multiple different publisher systems (e.g., multiple differentsearch engines). In this regard, via a single interaction, an entityuser (e.g., a company) can update entity data by updating, adding,modifying, changing, etc. data associated with a first entity type andhave a corresponding data update executed with respect to other entitytypes that are associated with the first entity type by one or moreestablished relationship types. This enables the entity data to beupdated across multiple different publisher systems to establishuniformity and consistency in the type, quality, and accuracy of theentity data returned by the different publisher systems to an end userin response to a query.

FIG. 1 illustrates an example environment 10 including a knowledgesearch system 100 operatively coupled to one or more merchant systems101. In one embodiment, the knowledge search system 100 enables a user(herein referred to as a “merchant user”) operating a communicativelyconnected merchant device 102 on behalf of the merchant system 101 toenhance one or more business listings associated with the merchant inaccordance with one or more aspects of the disclosure.

According to embodiments, the knowledge search system 100 includesmodules configured to perform various functionality, operations,actions, and activities, as described in detail herein. In anembodiment, the knowledge search system 100 includes an entity typemanager 110, a search experience management component 120, and aknowledge search engine 130 operatively coupled to one or moreprocessing devices 140 and a memory 150. In an embodiment, the memorycan include a knowledge search system database configured to store datarelating to the knowledge search system 100. In one embodiment, thesoftware modules may be executed on one or more computer platforms ofthe knowledge search system that are interconnected by one or morenetworks, which may include the Internet. The software modules may be,for example, a hardware component, circuitry, dedicated logic,programmable logic, microcode, etc., that may be implemented by aprocessing device 140 executing instructions stored by the memory 150 ofthe knowledge search system 100.

In some embodiments, the knowledge search system 100 may generateenhanced business listings for provisioning to an end user system 170 inresponse to one or more search queries 172 initiated by the one or moreend user systems 170 via an interface operatively coupled to theknowledge search engine 130 of the knowledge search system 100. In anembodiment, the search queries 172 can be submitted by one or more enduser systems 170 via an interface of the knowledge search system 100,the merchant system 101, and the one or business listing providersystems 180 (e.g., third-party search engines, websites, orapplications, such as Google®, Yelp®, Bing®, etc.). As used herein, theterm “end user” refers to one or more users operating an electronicdevice (e.g., end user system 170) to submit a search query 172 to asystem (e.g., the merchant system 101, the knowledge search system 100,a business listing provider system 180) to obtain search resultsassociated with a merchant. For example, the end user system 170 mayinitiate a search by entering a search query via an interface of awebpage of the merchant system 101. In an embodiment, the search resultsare generated based on merchant information managed by the knowledgesearch system 100.

In an example, the end user system may be a customer or prospectivecustomer searching for information about one or more merchants. In anembodiment, the knowledge search system 100 may be communicativelyconnected to the end user system 170 and operates to respond to a searchquery 172.

In an embodiment, the knowledge search system 100 is operatively coupledto the one or more merchant systems 101, the one or more end usersystems 170, and the business listing provider systems 180 via asuitable network (not shown), including, for example, the Internet,intranets, extranets, wide area networks (WANs), local area networks(LANs), wired networks, wireless networks, or other suitable networks,etc., or any combination of two or more such networks. In oneembodiment, the knowledge search system 100 includes a processing device140 and a memory 150 configured to execute and store instructionsassociated with the functionality of the various components, services,and modules of the knowledge search system 100, as described in greaterdetail below in connection with FIGS. 1-11.

In one embodiment, the merchant system 101 may include one or morecomponents of the knowledge search system 100. In this embodiment, themerchant system 101 and the knowledge search system 100 may beintegrated such that the merchant system 101 employs the knowledgesearch system 100 and its related functionality to respond to one ormore search queries 172 received from a communicatively connected enduser system 170. According to embodiments of the present disclosure, asshown in FIG. 1, the user device 130 may submit a search query 172 tothe merchant system 101 (wherein the merchant system 120 is integratedwith the knowledge search system 100) and/or submit a search query 172associated with the merchant system 120 to the knowledge search system101.

The merchant, via the merchant system 101, may use the knowledge searchsystem 100 to manage its data (also referred to as “merchant data”) onthe knowledge search system 100 and “push” or otherwise provision thatmerchant data to the end users (e.g., customers) in response to thesearch queries 172 and/or “push” or otherwise provision the merchantdata to one or more business listing providers systems 180. In thatregard, the merchant system 101 controls the data that is being returnedto the end user from the knowledge search system 100. In otherembodiments, at least a portion of the merchant data may be “pulled” orotherwise received from another system, such as a website associatedwith the merchants or other type of search websites. In one embodiment,the merchant user uses the merchant system 101 to communicate with theknowledge search system 100 to request changes to merchant data (e.g.,data that may be provided to an end user in response to an associatedinput query 140).

In some embodiments, the merchant system 101 and business listingprovider systems 180 include one or more modules (e.g., APIs) with whichthe knowledge search system 100 interacts for carrying out operationsand providing relevant merchant data to the end user systems 170. Forexample, the merchant system 101 and business listing provider systems180 may include APIs to access one or more prescribed databasesdedicated to storing information (e.g., merchant data) regarding theproducts, services, employees, events, etc. of a particular merchant. Inother embodiments, the knowledge search system 100 may include adatabase storing all or a portion of the merchant data. For example, theknowledge search system 100 may include one or more prescribed databasesdedicated to storing the information related to the merchant data.

As shown in FIG. 1, the knowledge search system 100 may include multiplemodules executed on one or more computer platforms that areinterconnected by one or more networks, which may include any suitablenetwork, such as the Internet. In some embodiments, the modules mayinclude one or more hardware components, circuitry, dedicated logic,programmable logic, microcode, etc., and one or more sets ofinstructions executable by one or more processing devices of theknowledge search system 100. The modules may include, for example, (1)an entity type manager 110 configured to enable merchant systems 101 toestablish customized entity types and relationship types associatingmultiple entity types as it relates to the merchant data, (2) a searchexperience management component 120 to enable a merchant system 101 toconfigure or customize a set or collection of input fields to define asearch experience that can be presented to and used by an end usersystem 170 to conduct a search relating to the merchant (e.g., whereinthe search experience is provided to the end user via an interface of awebsite of the merchant system), (3) a knowledge search engine 130 toprovide enhanced website searches by analyzing a search query initiatedby an end user system 170 to identify a natural language inquiryassociated with questions about a particular merchant (e.g., merchantdata relating to products, services, employees, events, locations,etc.).

In an embodiment, the knowledge search system 100 is configured tocommunicate with the merchant systems 101, the end user systems 170, andthe business listing provider systems 180 across various specializedtechnologies based on such factors, as distance, prominence, traffic,cultural relevance, industry relevance, event type relevance, directoryversus editorial sites, paid versus free, long-term versus last-minuteplanning, etc.

The entity type manager 110 allows merchant systems 101 (e.g., merchantusers) to interact with the knowledge search system 101 to performvarious operations, such as, for example, generating customized entitytypes associated with the merchant data and establishing relationships(i.e., relationship types) between multiple different entity typesassociated with the merchant data.

In an embodiment, an end user may use a user device 130 to submit asuggested or requested change or edit to a portion of the merchantinformation provisioned to the end user in response to a search query172 (e.g., the end user may suggest a change to the operating hours ofthe merchant if the end user determines that the published hours areincorrect). In response, the knowledge search system 100 reviews theproposed or suggested change and provides the change request to themerchant system. In an embodiment, the knowledge search system 100 canupdate information associated with a merchant and provide a notificationof the update or change to the merchant system 101. In an embodiment,the knowledge search system 100 collects updated information associatedwith the merchant and provide the updated information to the merchantsystem 101 for review and approval prior to adoption of the update orchange.

In some embodiments, the knowledge search system 100 enables merchantusers to interact with their end users via conversational user interface(UI). The merchant users may opt-in to this feature of the knowledgesearch system 100 by entity and/or by interaction type. In someembodiments, the merchant users add a phone number and/or accountinformation for each interaction type on the entity (without associatingto user). In some embodiments, the knowledge search system 100 mayauto-enable the merchant system for certain account types or businessesand use customer matching API to collect social media-relatedinformation about the merchant user (e.g., an end user's Facebook™identifier). In an embodiment, in response to the knowledge searchsystem 100 registering a location with a merchant with and confirmingthat the merchant user has a validated phone or social media accountlinked (depending on the interaction type), the knowledge search system101 may engage with the merchant user on the associated social networkplatform.

According to an embodiment of the present disclosure, the knowledgesearch engine 130 executes searches based on input from the end user(e.g., search queries 172 submitted by an end user system 170 via aninterface operatively coupled to the knowledge search system 100). Inone embodiment, the search may be conducted based on informationinputted by the end user (e.g., their zip code, geolocation or otherinformation that could lead to the determination of the end user'slocation and/or location of interest). In another embodiment the searchmay be based on where the end user (e.g., the user device 130) issearching from (for example, the user device's IP address is queried andused in connection with the search). The knowledge search engine 130 mayassess the search results to provide recommendations to the merchantuser. In one embodiment, the recommendation may be presented to themerchant system 101 as a notification provided by the knowledge searchsystem 100.

In another embodiment, the knowledge search system 100 provides one ormore recommendations to a merchant system 101 to improve the content ofsearch results relating to the merchant, as described in detail herein.For example, a search of competitor information published in indexedsearch engine databases may be performed by the knowledge search engine130. For example, the knowledge search system 100 can determine that acompetitor associated with a merchant published several imagesassociated with the competitor's store in an applicable location. In anembodiment, the knowledge search system 100 can send a message (e.g., atext, electronic mail, etc.) to one or more merchant devices 102associated with the merchant system 101 recommending that the merchantadd photos to an applicable business location corresponding to thecompetitor's place of business. Upon input from the merchant system 101,the knowledge search system 100 may upload photos to one or morebusiness listing provider systems 180.

According to embodiments, the knowledge search system 100 can generateor more interfaces to enable an end user system 170 to perform a searchfor information. In an embodiment, the one or more interfaces presentedby the knowledge search system 100 to an end user system 170 (e.g., viaa graphical user interface of a user device employed by the end user)may provide one or more of the following features: 1) performingreal-time auto-completion responsive to input entry by the end user(e.g., as the end user types or otherwise enters (e.g., voice dictation)his or her search query) in an example range of less than 100 ms, lessthan 50 ms, etc.; 2) generating of responsive result cards (e.g., one ormore responses to an end user search query including locationinformation including maps, events associated with a merchant, etc.); 3)providing a single-search interface (e.g., a single box) to enable anend user to search for and identify multiple different types ofinformation using a single search query (e.g., a search initiated by asingle search action); 4) generating of search results based onincorrect or ambiguous search queries (e.g., a forgiving searchconfigured to manage misspellings and synonyms); 5) generating of aranked list of search results based on one or more ranking parametersconfigured to present the search result data in an optimized manner forconsumption by the end user; 6) generating search results including oneor more sections to differentiate the search results; 7) generating ofsearch results including highlighting of one or more “matched” searchterms; 8) conduct a search for properties relating to the search inaddition to related entities; 9) enabling keyboard navigation to allowthe end user to use arrow keys and enter to navigate a user-friendlysearch experience.

As shown in FIG. 1, the knowledge search system 100 can be operativelycoupled to one or more developer systems 105 to provide a developer withenhanced and improved functionality. In an embodiment, the knowledgesearch system 100 provides one or more developer systems 105 with aJavaScript library configured to wrap an associated applicationprogramming interface (API) to facilitate the display of an associateduser interface (UI). In an embodiment, the knowledge search systemprovides an improved API enabling a developer system 105 to make one APIcall to search all available databases and return results in astructured format. Advantageously, the aforementioned features enablethe knowledge search system 100 to reduce latency and costs experiencedby developer users employing a mobile device by reducing API calls andassociated processing time and resource expenditure.

FIG. 2 illustrates a flow diagram illustrating an example process 200including steps performed by a knowledge search system (e.g., knowledgesearch system 100 of FIG. 1) communicatively connected with a developeruser, according to embodiments of the present disclosure.

In block 210, the knowledge search system presents a search field to adeveloper user (e.g., a device or system operated by a user of thedeveloper system 105). In block 220, the knowledge search systemreceives a first input from the developer user. In an example, the firstinput may include one or more characters entered by the developer userin the provided search field.

In block 230, the knowledge search system generates a first set ofsearch results in response to the first input received from thedeveloper user. In an embodiment, the first set of search results mayinclude multiple result entries presented in a priority or ranked order.In an embodiment, the first set of search results may be derived basedon a review and analysis of information stored in one or more databases.In an embodiment, depending on the API, the returning of the first setof search results may require multiple complicated API queries to searchover multiple fields and entities.

In block 240, the knowledge search system displays the first set ofsearch results. In an embodiment, the search results may include arendered card for each result type. In one embodiment, the first set ofsearch results may be grouped into multiple sections. In one embodiment,portions of the search results that match a portion of the textassociated with the first input may be highlighted.

In block 250, the knowledge search system may receive a selection fromthe developer user of a first search result from the first set of searchresults. In an embodiment, the developer user may enter his or herselection using a mouse, keyboard, voice command, touchscreen, or otherinput device or mechanism. In response to the receipt of the selection,the knowledge search system may store the selection (block 260), executeanother search (e.g., show an advisor near a zip code, block 270) orredirect the developer user to an entity webpage (e.g., show eventdetails, block 280).

In an embodiment, in response to displaying the first set of searchresults in block 240, the knowledge search system may receive a secondinput (e.g., one or more new characters) from the developer user, inblock 255. In response to receipt of the second input, the process mayreturn to block 230 and continue as illustrated.

According to embodiments of the present disclosure, marketers areprovided with enhanced and improved functionality by the knowledgesearch system. In an embodiment, the knowledge search system providesone or more marketers with features and functionality to enable amarketer user to tune their search experience and refine theircorresponding search results. In an embodiment, the knowledge searchsystem provides the marketer users with fine-tuned search results basedon analytics that enable a marketer user to adjust the search results toimprove their quality. In an embodiment, this may be based on generatingan understanding of the search performance.

In an embodiment, the knowledge search system provides the marketerusers with the ability to change the manner in which the search resultsare returned or displayed. Conventionally, changing the way searchresults appear requires a developer to make changes to the UI or the APIcalls. However, that can become extremely tedious if changes are madefrequently.

In an embodiment, the knowledge search system makes the API call “dumb”.In an embodiment, instead of performing all of the logic around whichfields to search, which entities to search, what ranking to use, etc.,the knowledge search system moves that logic behind the API call. In anembodiment, then, within the knowledge search system, the marketer usercan control the search result details using the knowledge search systeminterface. In an embodiment, a search algorithm executed by theknowledge search system moves from the client side to behind the API(e.g., not visible to the front-end developer user), as illustrated inthe logical diagram of FIG. 3.

In an embodiment, the knowledge search system includes a JavaScriptlibrary, a search API to facilitate “easier” queries, and an improvedinterface (e.g., a knowledge search interface configured for display viaa dashboard) to enable search API configuration and analytics.

In an embodiment, the JavaScript library makes it easier to build asearch experience. In an embodiment, a user (e.g., a developer user, amarketer user, etc.) may provide an input, section headers and resultcards and the JavaScript library of the knowledge search system showsthe search results and manages the user interaction. In an embodiment,the JavaScript library may automatically send analytics back into theknowledge search system for further review and analysis.

In an embodiment, the knowledge search system may include a search APIthat allows an end user to search multiple fields and multiple entitiesof a collection of information (also referred to as a “knowledge graph”)in a single API call (e.g., a single search action in response to asingle indication by the end user system). In an embodiment, the searchexperience management component 120 of the knowledge search system 100can be used by a merchant system 101 to configure a search experienceinterface defined by multiple input fields and entity types that aresearched in a single API call. In an embodiment, the knowledge searchsystem may employ one or more API filters to enable an end user toengage with a search experience interface to execute a search acrossmultiple fields and multiple entities in a single API call. In anexample, the API call itself is “dumb” and may be structured accordingto the following example structure:

{ searchInstance: “primary”, query: “onward”, }In some embodiments, the knowledge search system 100 allows merchantsystems 101 to generate one or more search experience interfaces whichinclude curated search results that are displayed to an end user system170 in response to a search query 172. In an embodiment, a searchexperience interface (also referred to as a “think experience” or “thinkexperience interface”) can include a collection of input fields (e.g.,identified based on input from the merchant system 101) configured toreceive search terms from an end user system as part of a search query.In some embodiments, different search experience interfaces can becreated for different webpages on a merchant website. For example, amerchant user may create a first search experience interface for amerchant store locator webpage, a second search experience interface fora merchant menu item finder webpage and a third search experienceinterface for a merchant event calendar webpage. According toembodiment, a merchant system 101 can create multiple different searchexperience interfaces using the search experience management component120 to deploy via multiple webpages of the merchant system 101 for useby the end user systems 170.

In an embodiment, one or more different data types can be used togenerate a search experience interface including multiple differentinput fields. In some embodiments, an example data type that can be usedto define a search experience interface is one or more input fields. Inan embodiment, an input field is a group of searchable attributes. In anembodiment, the one or more input fields of a search experienceinterface can be used to control and manage the input of text associatedwith a search query inputted via a web page. For example, an input fieldcan be a location selector or a search across an entire knowledge graph(i.e., collection of information). In some embodiments, each searchexperience interface can contain multiple input fields.

In some embodiments, an input field of a search experience interface caninclude one or more parameters. In an embodiment, a parameter representsthe type of data that can be searched across in a corresponding inputfield. In an embodiment, each input field includes at least oneparameter. Example parameters can include a name, an entity type (e.g.,specialty, condition, etc.), an address, etc.

FIG. 4 illustrates an example search experience interface 400 generatedby the knowledge search system, according to embodiments of the presentdisclosure. As shown, the search experience interface 400 includesmultiple input fields (e.g., a ‘location’ input field 410 and a‘provider’ input field 420) configured to receive one or more searchterms relating to the input field category (e.g. location, provider,specialty, etc.). In an embodiment, for each input field 410, 420, anend user can select or input one or more search terms associated withthe multiple different parameters 412, 422. For example, the locationinput field 410 is configured to enable the input of search criteriaagainst a first set of parameters 412 (e.g., Parameter 1, Parameter 2,and Parameter 3) and the provider input field 420 is configured toenable the input of search criteria against a second set of parameters422 (e.g., Parameter X, Parameter Y, and Parameter Z). In an embodiment,upon execution of a single search can be initiated via a single searchaction, such as an interaction with the search action button 430. Thesingle search can be executed for the illustrated search experienceinterface 400 against or using the search terms (e.g., the searchcriteria) provided for the parameters of multiple input fields. It isnoted that a given input field can be associated with any number ofparameters, and any number of input fields can be used to generate asearch experience interface.

FIG. 5 illustrates an example generation of a search experienceinterface by the knowledge search system of the present disclosure. Asshown in FIG. 5, a merchant system (e.g., merchant system ABC 501)interacts with the knowledge search system 500 to generate a searchexperience interface for use with one or more webpages or otherinterfaces associated with the merchant system ABC 501. In this example,the knowledge search system 500 generates a “Find a Provider” searchexperience type. In an embodiment, the merchant system ABC 501 selectsthe following input fields to be included in the “Find a Provider”search experience interfaces: a “Location” input field (i.e., InputField 1 in FIG. 5) and a “Provider” input field (i.e., Input Field 2 inFIG. 5). In an embodiment, the merchant system ABC 501 selects one ormore parameters to associate with each of the input fields (Input Field1 and Input Field 2). In the example shown, a “City, Zip, Place”parameter field is associated with the Location Input Field. Inaddition, the Input Field 2 is associated with the following parameters:provider type, condition, specialty, provider name, and practice name.Advantageously, in an embodiment, the parameters can be used to refinethe search experience via their association with the corresponding inputfield. In an embodiment, the input fields and corresponding parametersare displayed to the end user system via the search experienceinterface. The end user can enter or select one or more search terms foreach of the input fields to submit a search query for processing by theknowledge search system.

In an embodiment, the search experience interface associated with the“Find a Provider” search experience can be presented to an end usersystem via one or more webpages or application pages associated with themerchant system ABC 501. The end user can generate a search query byproviding information in the multiple input fields via the searchexperience interface. In an embodiment, the knowledge search system 500can return one or more search results (e.g., a set of search results)corresponding to the search query.

As described above, in an embodiment, a search experience can have oneor more input fields. In another embodiment, the search experienceinterface can be defined and established without an input field. In anembodiment, an input field can be associated with one parameter. In anexample, a marketer user can adjust how an input field operates, withoutworking with a developer user. For example, the marketer user can add asecond searchable input field to a search experience interface. In anembodiment, the knowledge search system can generate and process queryanalytics associated with each of the input fields to generate analyticsdata associated with search queries executed using the input fields.

As described above, when setting up an input Field, a merchant systemcan select a set of parameters to include with the input field. In anembodiment, when viewing analytics, a merchant system can employ the setof parameters and one or more additional “filters” that are included viaAPI. For example, if a user employs the knowledge search system tocollect analytics data, where no input fields are employed, the one ormore parameters (e.g., filters) can be presented via the interface.

In an embodiment, the one or more parameters may be identified by colorsin the user interface. The merchant system can configure parameters(filters) that are displayed in association with the one or more inputfields with a uniform color scheme, wherein the parameter has the samecolor across multiple different webpages of the merchant system.

In some embodiments, the knowledge search system can include a programlibrary (e.g., a Javascript library), a user interface for configurationand analytics, and multiple API endpoints. In some embodiments, theprogram library can be used to build the search experience andcorresponding search experience interface. In some embodiments, themerchant system can be given an input, section headers and result cardsand the library will handle showing the results and the userinteraction. Additionally, this program library may send analytics backinto the knowledge manager 168.

In some embodiments, the data stored in a database associated with theknowledge search system may automatically be synced to a websiteassociated with the merchant system in response to an end user systemsubmission of a search query via a user device, based on the searchexperience created.

FIG. 6A illustrates an example interface of the knowledge search systemconfigured to enable a merchant user to manage, change, create, andupdate one or more search experience types and search experienceinterfaces. As shown, a merchant user representing a merchant system(e.g., Merchant ABC) can login to the knowledge search system to view adisplay of the one or more search experiences associated with an accountof the merchant system. As shown in this example, Merchant ABC has fouractive search experiences: a “Find a Doctor” search experience, a “Finda Hospital” search experience, a “Find Homecare and Hospice” searchexperience, and a “Find an Insurance Plan” search experience. For eachsearch experience, the search experience name or label and one or morecorresponding input fields are displayed. In an embodiment, each of theinput fields can have one or more parameters that are either selected bythe merchant system or default parameters set by the knowledge searchsystem.

FIG. 6B illustrates an example interface generated by the knowledgesearch system to enable a merchant system to generate or create a newsearch experience. In an embodiment, the merchant user can select a newsearch experience from a list of pre-built templates or example searchexperiences (e.g., an “All Entities Finder” template, a “Doctor Finder”template, an “Event Calendar” template, a “Financial Advisor Finder”template, a “Menu Item Finder” template, a “Service Near Me Finder”template, and a “Store Locator” template) or select an option to createa custom search experience (e.g., a “Custom Search Experience”template). In an embodiment, in response to a selection of a searchexperience template, the knowledge search system provides thecorresponding template.

In an embodiment, if the merchant user selects the “Custom SearchExperience” template, the knowledge search system provides a prompt forthe merchant user to select information associated with the customsearch experience, including a search experience name, a searchexperience or API key, a search experience description, and a list ofone or more entity types that are be searched against in response to enduser queries submitted using the custom search experience. Following theselection of a pre-built search experience or a custom search experience(as shown in FIG. 6C), the knowledge search system generates a searchexperience interface or page.

FIG. 6D illustrates an example interface generated by the knowledgesearch system configured to allow a merchant user to review and managesearch experiences. As shown, the knowledge search system presents thesettings associated with a search experience (e.g., the name,description, listing of information entities to query, etc.) and thecorresponding input fields of the search experience interface. In thisexample, Input Field 1 is a “Location” input field having a “Location”parameter. Input Field 2 is a “Provider” input field having a set ofparameters including “Doctor name”, “Condition”, “Specialty”,“Language”, “Practice name”, and “Symptoms” parameters. As shown in FIG.6D, the knowledge search system displays a “live preview” of the searchexperience where the merchant user can test the search experience byinteracting with the input fields to execute a query to obtain searchresults. As shown, the merchant system can add a new input field ordelete an existing input field associated with a search experience viathe interface of the knowledge search system. In an embodiment, themerchant system can add or delete a parameter associated with each ofthe input fields.

FIG. 6E illustrates an example interface generated by the knowledgesearch system to enable a merchant system to edit or modify a searchexperience. In this example, the merchant system interacts with theinterface to configure settings for the parameters associated with the“Provider” input field. As shown, the return value associated with eachof the parameters and the typographical error (or “typo”) tolerance canbe set. In an embodiment, the search experience can be customizedwithout any specific input field. This “empty” search experienceincludes a generic or non-specific search field to enable an end user tosubmit a search query.

In some embodiments, the knowledge search system 100 may store (via oneor more databases) the search queries of end users and present them asanalytics to merchant systems. According to an embodiment, the knowledgesearch system 100 may allow a merchant system 101 to configure and aview analytics about a search experience. In an embodiment, a knowledgesearch may be provided via a tab under a “search” tab. In an embodiment,a merchant user may set up new search instances, determine which entitytypes and fields are searched, identify the matching logic, andconfigure the manner in which the search results should be ranked, asshown in FIG. 7A (e.g., analytics of a search instance). FIG. 7Billustrates an example interface relating to configuration of an examplesearch bar.

In an embodiment, a search bar instance according to the knowledgesearch system may include analytics information and configurationinformation. Example analytics information may include one or more ofthe following: 1) hero numbers (e.g., total searches, average number ofresults, average response time, time to result, etc.); 2) high-levelmetrics over a period of time (e.g., number of searches over the periodof time—such as, by platform (e.g., phone, tablet, desktop, etc.)),average response time, etc.); 3) a listing of frequently or commonlyselected options; 4) a listing of frequently or commonly selectedqueries (e.g., condensed queries wherein not every character typed ispresented; presenting most popular and most popular without results andmost popular with no result selected).

In an embodiment, example configuration information may include one ormore of the following: 1) searchable attributes; 2) other configurablesettings such as API key, answer box key, group results in sections,etc.) In an embodiment, the knowledge search system may provide amerchant marketer user with one or more of the following features: 1)search as you type functionality; 2) single search across multipleentities and attributes; 3) fast and efficient searching; 4) a tailoredor customizable experience depending on a given use case. In anembodiment, the knowledge search system may provide a marketer user withone or more of the following analytics based at least in part feedbackdirectly from consumer or end users: 1) a description of how end userssearch; 2) a description of what end users care about; 3) identificationof opportunities to improve searches; 4) identification of opportunitiesto improve business practices.

According to embodiments, users have a greater degree of control, ascompared to conventional systems that rely on IT. For example, a usercan configure what is showing up and modify results without developersor additional IT resources. FIG. 8 illustrates an example interfacegenerated by the knowledge search system, according to embodiments ofthe present disclosure. FIG. 8 illustrates an example interface relatingto a view of multiple search instances (e.g., all available searchinstances).

In an embodiment, the knowledge search system (e.g., the entity typemanager 110 of the knowledge search system 100 shown in FIG. 1) enablesmerchant systems to establish a knowledge graph including multipleentity types (e.g., custom or system-defined) associated by one or morerelationship types. The knowledge graph represents the information todata relating to the merchant system which is maintained, updated, andstored in the one or more data fields of the entity types associatedwith the merchant system. In an embodiment, an update to a first entitytype in the knowledge graph can be distributed to one or more otherentity types within the knowledge graph based on the relationship typesdefined between the multiple entity types.

FIG. 9A illustrates a flow diagram of a method 900 to generate arelationship type associating multiple entity types to manage updates ina knowledge graph associated with a merchant system, according toembodiments of the present disclosure. The method 900 can be performedby processing logic that can include hardware (e.g., processing device,circuitry, dedicated logic, programmable logic, microcode, hardware of adevice, integrated circuit, etc.), software (e.g., instructions run orexecuted on a processing device), or a combination thereof. In someembodiments, the method 900 is performed by the entity type manager 110of the knowledge search system 100 of FIG. 1. Although shown in aparticular sequence or order, unless otherwise specified, the order ofthe processes can be modified. Thus, the illustrated embodiments shouldbe understood only as examples, and the illustrated processes can beperformed in a different order, and some processes can be performed inparallel. Additionally, one or more processes can be omitted in variousembodiments. Thus, not all processes are required in every embodiment.Other process flows are possible.

As illustrated, at operation 910, the processing logic generates a firstentity type associated with a merchant system, where the first entitytype includes one or more first data fields including first datacorresponding to the merchant system. In an embodiment, the first entitytype can be a custom entity type (e.g., established and configured by amerchant system) or a built-in or system-defined entity type. The firstentity type can include one or more data fields including data (e.g.,data values) associated with the merchant system.

At operation 920, the processing logic generates a second entity typeassociated with the merchant system, where the second entity typeincludes one or more second data fields comprising second datacorresponding to the merchant system. As noted above, the second entitytype can be a custom entity type or a system-defined entity type. Likethe first entity type, the second entity type is configured to includeone or more data fields to store data associated with the merchantsystem. An example of a first entity type (e.g., the “Restaurant” entitytype) and a second entity type (e.g., the “Menu” entity type) is shownin FIG. 9B.

At operation 930, the processing logic establishes a relationshipbetween the first entity type and the second entity type, wherein atleast a first portion of the first data matches at least a secondportion of the second data. In an embodiment, the relationship isdefined by a relationship type which links or associates multiple entitytypes. For example, as shown in FIG. 9B, the “Offered at” relationshiptype establishes a defined relationship between the first entity type(“Restaurant”) and the second entity type (“Menu”). In an embodiment,the relationship type defines the nature of the association betweenmultiple entity types and can be used to identify additional entitytypes to be updated in response to the updating of an entity type. In anembodiment, the relationship type can represent that multiple entitytypes share data (e.g., at least a portion of the data fields of themultiple entity types match one another).

At operation 940, the processing logic receives, from the merchantsystem, an update to the first portion of the first data of the firstentity type. In an embodiment, the update to the first portion of thefirst data can include a deletion, correction, addition, reformat,change, etc. of one or more data values of the one or more data fieldsof the entity type. In an embodiment, the update to the first entitytype can be executed via a communication or interaction between themerchant system and the knowledge search system.

At operation 950, the processing logic generates an updated first entitytype including the update to the first data. In an embodiment, theupdated first entity type is generated and stored in association withthe merchant system.

At operation 960, in view of the relationship between the first entitytype and the second entity type, the processing logic updates the secondportion of the second data of the second entity type to generate anupdated second entity type. In an embodiment, the processing logic can,in response to the update to the first entity type, identify therelationship type between the first entity type and one or more otherentity types, including the second entity type. The processing logic canuse the relationship type to identify the match between a least aportion of the data of the first entity type and the data of the secondentity type. In an embodiment, in this regard, the relationship type canbe used to determine if the second entity type is to be updated in viewof the update to the first entity type. It is noted that an entity type(e.g., the first entity type) can be associated with multiple otherentity types by one or more different relationship types, as shown inthe example of FIG. 9C. Advantageously, via a single interaction by themerchant system (e.g., the updating of the first data of the firstentity type), one or more other entity type (e.g., the second entitytype) can be updated to include the updated data, in view of therelationships types linking the entity types in the knowledge graphassociated with the merchant system. In an embodiment, thisadvantageously enables a merchant system to initiate and make the updatein a single stored location (e.g., the first entity type) and have theupdate distributed and “pushed” to other entity types within theknowledge graph.

At operation 970, the processing logic stores, in a data store, theupdated first entity type and the updated second entity type. In anembodiment, the processing logic can distribute the updated first entitytype and the updated second entity type to one or more third-partysystems (e.g., business listing provider systems 180 of FIG. 1).Advantageously, the update to a first entity type can be linked to andshared to another entity type based on the established relationship.Additionally, the updated entity types can be distributed to multipledifferent third party systems (e.g., search engines, websites, etc.)such that a single update (e.g., the update to the first entity type)can result in the update to another entity type and updating of theinformation associated with a merchant in multiple different locations.

FIGS. 9B-9C illustrate example interfaces generated by the knowledgesearch system to enable interactions with a merchant system to generateand manage custom entity types. The various example interfaces shown inFIGS. 9B-9C illustrate various features and functionality associatedwith the knowledge search system, as described in greater detail below.

In an embodiment, the knowledge search system may include a large numberof built-in (e.g., system-defined) entity types relating to multipledifferent base types (e.g., person, location, service, etc.) In anembodiment, the system-defined entity types can be specialized byvertical (e.g., person>doctor, location>healthcare professional,service>procedures for Healthcare, etc.). In an embodiment, thesystem-defined types are established in response to the knowledge searchsystem coupling to a publisher network.

In an embodiment, the knowledge search system provides system-definedentity types and custom entity types. In an embodiment, the knowledgesearch system provides inheritance functionality which enables entitytypes (either system-define or custom) to build on other entity types.In an example, the knowledge search system can categorize the entitytypes to enable an “answer” (i.e., search result) to an example searchquery of: get me all people entities for my org, wherein the org is setup with: staff, executive, engineer, etc.

In an embodiment, the knowledge search system enables merchant systemsto store data about the entity types and define how the entity types arerelated by establishing associated relationship types between multipleentity types. For example, a first entity type (“doctor”) can beassociated with a second entity type (“location”) by a firstrelationship type (“works at”) to link or relate the multiple entitytypes. In addition, in this example, the first entity type (“doctor”)can be associated with a third entity type (“medical procedure”) by asecond relationship type (“specializes in”) to link the first entitytype and the third entity type. In this example, the knowledge searchsystem generates a mapping or association between the multiple entitytypes in view of the identified relationship type to establish thefollowing relationships: a doctor “works at” a location and “specializesin” a medical procedure. In an embodiment, the knowledge search systemcan add a custom entity type (at the direction of a merchant system) andcan monitor and observe how merchant systems interact with the knowledgesearch system to track how the merchant systems manage the custom entitytypes and the relationships between the entity types.

In some embodiments, a merchant system can create custom entity typesand relationships between multiple entity types (e.g., custom or builtin entity types). For example, in FIG. 9A, a merchant system caninteract with the knowledge search system to manage entity types andcorresponding relationship types. In an example, the merchant system canestablish a relationship (“Offered at”) between a first entity type(“Restaurant”) and a second entity type (“Menu”). In an embodiment, thefirst entity type and the second entity type can be system-definedentity types, custom entity types, or a combination thereof.

FIG. 9B illustrates an example set of entity types linked together byrelationships, generated in accordance with embodiments of the presentdisclosure. In an embodiment, the knowledge search system establishesthe multiple entity types (e.g., “Offer”, “Restaurant”, “Event”, “Jobs”,“Menu”, and “Menu item”) and establishes multiple relationships (e.g.,“Offered at”, “Position at”, “Promoted at”, “Available on”, “Availableat”) between different pairs of the entity types. For example, theentity type labeled “Jobs” can be a system-defined entity type and theentity type “Offers” can be a custom entity type. In an embodiment, amerchant system can create a custom entity type for limited time offersfor specific restaurants. Those limited time offers may be discounts ofcertain menu items (e.g., free French fries with any purchase of ahamburger) offered at certain restaurants. A merchant system can definewhich restaurants (e.g., the relationship between the restaurant andoffer entity types) those offers are offered at (e.g., all, a subset,etc.), and which menu items are involved in such offer (e.g.,relationship between menu items and offer).

In some embodiments, if the offer changes (e.g., free soda with anypurchase of a hamburger), a merchant system can update the correspondingentity type (e.g., the offer entity type). For example, if a merchantsystem changes the offer in the “Offers” entity type, that offer isautomatically changed in connection with the restaurants the offer isoffered at and the menu items by virtue of the established relationshipbetween the entity types.

In an embodiment, if a merchant has a different first party web page fora menu, limited time offer and restaurant locations, that informationcan be automatically updated across all web pages. In an embodiment, themerchant information can be updated in the one or more databases of theknowledge search system across the one or more entity types associatedwith the merchant system. For example, the menu can be updated to showthe new limited time offer, the particular restaurant locations wherethe offer is offered can be updated (e.g., via a corresponding API) todisplay the new offer, and the limited time offer webpage can be updatedto display the new offer. In other embodiments, the knowledge searchsystem can update the information across third-party websites (e.g.,online listing publishers, search engines, etc.), for example, via acorresponding API, in response to the update of the information type bythe merchant system. FIG. 10 illustrates an example interface generatedby the knowledge search system to enable a merchant system to create,update, and manage a custom information type, according to embodimentsof the present disclosure. In an embodiment, the knowledge search systemcan generate relationship types to relate entity types usingunidirectional linked custom field types as either standalone or as partof a custom field type that contains other properties. In an embodiment,the knowledge search system includes system-defined entity types andrelationships based on consumer feedback and observations. For example,the knowledge search system is configured to provide informationrelating to example analytics including, but not limited to: whatmotivates a customer to add an entity to the knowledge search system;when does some information deserve to be an entity type versus aproperty of another entity type; what entity types the various merchantsystems generate, use, and store in the knowledge search system; howrelationship types are used in the knowledge search system; whetherrelationship types can be converted to entity types to containadditional data or are relationship types properties of an entity type;the data the merchant systems store relating to do customers want tostore about their entities; how merchant systems use entity types indownstream end-user facing services, etc.

In an embodiment, custom entity types can be used to enable storage ofdata in the knowledge search system to enable merchant systems to usethe custom entity types with one or more other example systems andfeatures: knowledge Pages, consulting pages, knowledge search, listings,reviews, and analytics.

In an embodiment, the knowledge search system may provide compatibilitybetween custom and built-in entity types. For example, if a merchantsystem user adds a custom entity type named “Vehicle” and the knowledgesearch system subsequently adds a built-in type for “Vehicle”, theknowledge search system may enable the merchant system to migrate ortake advantage of the functionality of the built-in type. In anembodiment, the knowledge search system enables merchant systems tomanage which entity types are enabled in their account. In anembodiment, the knowledge search system may provide a customer with arecommended custom entity type based on historical data relating to themanner in which other merchant systems create custom entity types. Insome embodiments, a merchant system can create custom records, such as,for example, records relating to limited time offers, dealership groups,or product launches to reflect everything that makes its brand unique.In an embodiment, in response to a merchant system adding a new employeeor creating a new special offer, the knowledge search system can updateall the corresponding relationships. In an embodiment, the knowledgesearch system can update one or more connected search experiences inresponse to a change in the information provided by the merchant system.

In some embodiments, a merchant system may create a custom entity typethat is not supported by one or more thirty party websites orapplications. In some embodiments, the knowledge search system canreview the custom entity type requested by the merchant system andrecommend an alternative built-in entity type that is supported by theone or more third-party websites or applications. In such instances, themerchant system can choose to migrate all of the data in the customentity type to the built-in entity type and synchronize that data andthe entity type with the third-party websites and applications. In otherembodiments, the knowledge search system can migrate all data from thecustom entity types to the supported built-in entity type andsynchronize the related data to the third-party websites orapplications.

In other embodiments, the knowledge search system can alter the datastructure on the third-party websites or applications to enable supportfor custom entity types. In such embodiments, the custom entity typesmay be “locked” so that the third-party websites cannot change thestructure. In other embodiments the knowledge search system can assessthe entity types of certain merchant systems to recommend those entitytypes to similar merchant systems. In some embodiments, therecommendations may be done based on a recommendation rule that iscreated to enable the sending of notifications to applicable merchantusers that manage such data on behalf of the merchant system.

In an embodiment, the knowledge search system provides functionalityrelating to custom entity types that enable a merchant system to create,update or delete one or more custom entity types. In an embodiment, theknowledge search system enables a merchant system to view, enable ordisable entity types in the merchant system account.

According to embodiments of the present disclosure, the knowledge searchsystem may provide custom entity types that are specific to a merchantaccount or sub-account. In an embodiment, a merchant system may defineone or more of the fields associated with the custom entity type. In anembodiment, the custom entity types may be available via one or more ofthe services (e.g., information edit, approvals, scheduled updates,templates, upload, export, knowledge search system API, Live API, MLProfiles, custom goals, advanced filters, etc.).

In an embodiment, the knowledge search system may provide a fieldregistry configured to enable entity types to be defined by a specificcategory (e.g., by business). In an example, fields may be handled basedon subscription features, like publisher fields. In an embodiment, theknowledge search system provides flexibility to support features thatenables users to make custom field types and custom fields available tosub-accounts.

In an embodiment, the knowledge search system provides for management ofinformation schema and management of entity types. In an embodiment,information schema is managed by establishing entity type propertiessuch that each entity type (e.g., built-in entity types and customentity types) have a corresponding set of properties. In an embodiment,for custom entity types, a merchant system can control one or moreproperties, such as, for example, the following example properties:name, API name, description, entity type group, availability tosub-accounts, entity type icon, merchant system data, representation ofentity type in tabular form, fields, etc.

In an embodiment, one or more “fields” associated with a custom entitytype may be defined by a merchant system using the knowledge searchsystem. In an embodiment, after creating the entity type, the merchantsystem can view a list of available fields and select one or more fieldsto add to the entity type. In an example, by default, the entity typescan include the following fields: entity type identifier (ID) field anda name field.

In an embodiment, for additional fields of the custom entity type, themerchant system can perform one or more of the following actions: 1)specify whether the field is required for that type (e.g., a centralizednotion of required fields across all interfaces may be employed); and 2)specify whether the field should appear on the “Add” screen.

In an embodiment, merchant systems can view and enable or disableavailable entity types in their account. In an embodiment, the followingaspects may be considered: 1) determine whether the entity type issettable by the merchant system (e.g., determine whether the merchantuser can view it in a “manage entity type” table to enable or disable);2) if settable, determine whether the entity type is enabled or disabledin the account (e.g., determine whether the merchant system add aninstance of the entity type); 3) if enabled, determine which entity typeis the primary type in the account (e.g., determine the default type).

In an embodiment, if an entity type is “settable”, the merchant systemcan enable or disable the type in the knowledge search system. In anembodiment, there is a global setting for “settable,” (where anindication of “no” is used for entity types that are in testing), thatcan be managed for a particular business (with inheritance forsub-accounts where applicable) to enable the knowledge search system toturn entity types “on” for specific accounts for testing and hide entitytypes for merchant systems in certain instances.

In an embodiment, a merchant system can delete a custom entity type(e.g., if there are no unarchived instances of the type and the type isdisabled) such that the “customer settable” field is updated to “no”.

In an embodiment, for an entity type that is customer settable, amerchant system can enable or disable the type in the knowledge searchsystem. In an embodiment, given an entity type is enabled, each accountmay have a primary type. In an embodiment, a primary type can be set forsub-accounts.

In an embodiment, the knowledge search system can utilize the entitytypes that are generated and enabled to perform various operations andfunctions, including, for example, filtering based on entity type,generate templates for entity types, export entity types, upload customentity types, select an entity type, create a webpage for an entitytype, search for data relating to an entity type, add a user role inassociation with an entity type, generate analytics relating to theentity type, generate an activity report relating to an entity type,generate an entity type tree organized by group, etc.

According to embodiments of the present disclosure, natural languageprocessing may be performed using a knowledge graph, which can begenerated by the entity type manager 110. In an embodiment, theknowledge search system may suggest results in a drop down list based oninformation stored in a knowledge graph associated with a merchantsystem. For example, an end user may execute a search query for aninsurance agent that speaks a particular language. After the end usersearches for “agent that speaks” the drop down list is displayedincluding languages that are added to the knowledge graph by themerchant system. In an embodiment, the knowledge search system returnsan “answer” (e.g., search results responsive to the search query) in thedrop down list based on the information stored in the knowledge graphassociated with the merchant.

In an example, a merchant system may update their holiday hours in theirknowledge graph (e.g., Hours for New Year's Day=12 PM-3 PM). If an enduser customer initiates a search, on December 30th, “Holiday Hoursfor”—The results “Holiday Hours for New Year's Day=12 PM-3 PM” may bereturned in the drop down list, such that the end user does not have toexecute the full search (e.g., interact with or click a “search” buttonor link).

In another embodiment, search results can be returned in the form of adrop down list. In an example, a chat or structured map can be returned,and a “clicking” on the search link may not be needed.

In an embodiment, the knowledge search system may use analytics fromsearch data to power a notification or “knowledge nudge”. In anembodiment, analytics are displayed and used to provide recommendationsin the knowledge search system, such that merchant systems can set uprecommendation rules based on the recommendations provided by theknowledge search system. In an embodiment, an end user may conduct asearch on a merchant website—such as, looking for doctor specialties fora particular office of the merchant. In an example, the requestedinformation may not exist in the data graph associated with the merchantsystem. In this example, the knowledge search system may use analyticsto recommend updating that information and/or creating a notificationrule to remind other users (e.g., other offices associated with themerchant system) to update the “doctor specialties” information. In anembodiment, the knowledge search system may create a notification rulebased on the analytics and send it to the user (e.g., a merchant user)in charge of that information.

In another example, an end user may search for doctors in a particularlocation specializing in nutrition. In this example, if no informationis identified, a notification rule may be created to inform platformusers (e.g., merchant users) in particular locations to update thatinformation in their account.

FIG. 11 illustrates an example computer system 1100 operating inaccordance with some embodiments of the disclosure. In FIG. 11, adiagrammatic representation of a machine is shown in the exemplary formof the computer system 1100 within which a set of instructions, forcausing the machine to perform any one or more of the methodologiesdiscussed herein, may be executed. In alternative embodiments, themachine 1100 may be connected (e.g., networked) to other machines in alocal area network (LAN), an intranet, an extranet, or the Internet. Themachine 1100 may operate in the capacity of a server or a client machinein a client-server network environment, or as a peer machine in apeer-to-peer (or distributed) network environment. The machine may be apersonal computer (PC), a tablet PC, a set-top box (STB), a personaldigital assistant (PDA), a cellular telephone, a web appliance, aserver, a network router, switch or bridge, or any machine capable ofexecuting a set of instructions (sequential or otherwise) that specifyactions to be taken by that machine 1100. Further, while only a singlemachine is illustrated, the term “machine” shall also be taken toinclude any collection of machines that individually or jointly executea set (or multiple sets) of instructions to perform any one or more ofthe methodologies discussed herein.

The example computer system 1100 may comprise a processing device 1102(also referred to as a processor or CPU), a main memory 1104 (e.g.,read-only memory (ROM), flash memory, dynamic random access memory(DRAM) such as synchronous DRAM (SDRAM), etc.), a static memory 1106(e.g., flash memory, static random access memory (SRAM), etc.), and asecondary memory (e.g., a data storage device 1116), which maycommunicate with each other via a bus 1130.

Processing device 1102 represents one or more general-purpose processingdevices such as a microprocessor, central processing unit, or the like.More particularly, the processing device may be complex instruction setcomputing (CISC) microprocessor, reduced instruction set computer (RISC)microprocessor, very long instruction word (VLIW) microprocessor, orprocessor implementing other instruction sets, or processorsimplementing a combination of instruction sets. Processing device 1102may also be one or more special-purpose processing devices such as anapplication specific integrated circuit (ASIC), a field programmablegate array (FPGA), a digital signal processor (DSP), network processor,or the like. Processing device 1102 is configured to execute a knowledgesearch system 100 for performing the operations and steps discussedherein. For example, the processing device 1102 may be configured toexecute instructions implementing the processes and methods describedherein, for supporting a knowledge search system 100, in accordance withone or more aspects of the disclosure.

Example computer system 1100 may further comprise a network interfacedevice 1122 that may be communicatively coupled to a network 1125.Example computer system 1100 may further comprise a video display 1110(e.g., a liquid crystal display (LCD), a touch screen, or a cathode raytube (CRT)), an alphanumeric input device 1112 (e.g., a keyboard), acursor control device 1114 (e.g., a mouse), and an acoustic signalgeneration device 1120 (e.g., a speaker).

Data storage device 1116 may include a computer-readable storage medium(or more specifically a non-transitory computer-readable storage medium)1124 on which is stored one or more sets of executable instructions1126. In accordance with one or more aspects of the disclosure,executable instructions 1126 may comprise executable instructionsencoding various functions of the knowledge search system 100 inaccordance with one or more aspects of the disclosure.

Executable instructions 1126 may also reside, completely or at leastpartially, within main memory 1104 and/or within processing device 1102during execution thereof by example computer system 1100, main memory1104 and processing device 1102 also constituting computer-readablestorage media. Executable instructions 1126 may further be transmittedor received over a network via network interface device 1122.

While computer-readable storage medium 1124 is shown as a single medium,the term “computer-readable storage medium” should be taken to include asingle medium or multiple media. The term “computer-readable storagemedium” shall also be taken to include any medium that is capable ofstoring or encoding a set of instructions for execution by the machinethat cause the machine to perform any one or more of the methodsdescribed herein. The term “computer-readable storage medium” shallaccordingly be taken to include, but not be limited to, solid-statememories, and optical and magnetic media.

Some portions of the detailed descriptions above are presented in termsof algorithms and symbolic representations of operations on data bitswithin a computer memory. These algorithmic descriptions andrepresentations are the means used by those skilled in the dataprocessing arts to most effectively convey the substance of their workto others skilled in the art. An algorithm is here, and generally,conceived to be a self-consistent sequence of steps leading to a desiredresult. The steps are those requiring physical manipulations of physicalquantities. Usually, though not necessarily, these quantities take theform of electrical or magnetic signals capable of being stored,transferred, combined, compared, and otherwise manipulated. It hasproven convenient at times, principally for reasons of common usage, torefer to these signals as bits, values, elements, symbols, characters,terms, numbers, or the like.

It should be borne in mind, however, that all of these and similar termsare to be associated with the appropriate physical quantities and aremerely convenient labels applied to these quantities. Unlessspecifically stated otherwise, as apparent from the followingdiscussion, it is appreciated that throughout the description,discussions utilizing terms such as “identifying,” “determining,”“analyzing,” “selecting,” “receiving,” “presenting,” “generating,”“deriving,” “providing” or the like, refer to the action and processesof a computer system, or similar electronic computing device, thatmanipulates and transforms data represented as physical (electronic)quantities within the computer system's registers and memories intoother data similarly represented as physical quantities within thecomputer system memories or registers or other such information storage,transmission or display devices.

Examples of the disclosure also relate to an apparatus for performingthe methods described herein. This apparatus may be speciallyconstructed for the required purposes, or it may be a general-purposecomputer system selectively programmed by a computer program stored inthe computer system. Such a computer program may be stored in a computerreadable storage medium, such as, but not limited to, any type of diskincluding optical disks, CD-ROMs, and magnetic-optical disks, read-onlymemories (ROMs), random access memories (RAMs), EPROMs, EEPROMs,magnetic disk storage media, optical storage media, flash memorydevices, other type of machine-accessible storage media, or any type ofmedia suitable for storing electronic instructions, each coupled to acomputer system bus.

The methods and displays presented herein are not inherently related toany particular computer or other apparatus. Various general-purposesystems may be used with programs in accordance with the teachingsherein, or it may prove convenient to construct a more specializedapparatus to perform the required method steps. The required structurefor a variety of these systems will appear as set forth in thedescription below. In addition, the scope of the disclosure is notlimited to any particular programming language. It will be appreciatedthat a variety of programming languages may be used to implement theteachings of the disclosure.

It is to be understood that the above description is intended to beillustrative, and not restrictive. Many other embodiment examples willbe apparent to those of skill in the art upon reading and understandingthe above description. Although the disclosure describes specificexamples, it will be recognized that the systems and methods of thedisclosure are not limited to the examples described herein, but may bepracticed with modifications within the scope of the appended claims.Accordingly, the specification and drawings are to be regarded in anillustrative sense rather than a restrictive sense. The scope of thedisclosure should, therefore, be determined with reference to theappended claims, along with the full scope of equivalents to which suchclaims are entitled.

What is claimed is:
 1. A method comprising: generating, in a knowledgegraph comprising a plurality of entity types storing data associatedwith a merchant system, by a processing device, a first entity typeassociated with a first category of data associated with the merchantsystem, wherein the first entity type comprises a first data fieldstoring a first data value corresponding to the first category and themerchant system; generating, in the knowledge graph, a second entitytype associated with a second category of data associated with themerchant system, wherein the second entity type comprises a second datafield storing a second data value corresponding to the second categoryand the merchant system, wherein the first entity type and the secondentity type are searchable in response to a query relating to themerchant system; establishing a relationship between the first entitytype and the second entity type, wherein the relationship is defined bya relationship type selected by the merchant system; receiving, from themerchant system, a first update to the first data value of the firstentity type; generating an updated first entity type comprising thefirst update to the first data value; determining based on therelationship type between the first entity type and the second entitytype, that the second entity type is to be updated in view of the firstupdate; generating, in view of the determining, a second update to thesecond data value of the second entity type; and storing, in theknowledge graph, the first update of the first entity type and thesecond update of the second entity type.
 2. The method of claim 1,further comprising distributing the first update and the second updateto a plurality of business listing provider systems.
 3. The method ofclaim 2, wherein the plurality of business listing provider systems areconfigured to provide the first update of the first entity type and thesecond update of the second entity type to an end user system.
 4. Themethod of claim 3, wherein the first update and the second update areprovided to the end user system in response to a search query from theend user system.
 5. The method of claim 1, further comprising:establishing a plurality of relationships between the first entity typeand a plurality of additional entity types; and in view of the pluralityof relationships, updating the plurality of additional entity types inresponse to the first update to the first data value of the first entitytype.
 6. The method of claim 5, further comprising: receiving an updateto an additional data value of a first additional entity type of theplurality of additional entity types; and in view of a relationship typebetween the first additional entity type and the first entity type,updating the first entity type.
 7. A system comprising: a memory tostore instructions; and a processing device operatively coupled to thememory, the processing device to execute the instructions to: receive afirst selection from a merchant system of a first input field, whereinthe first input field is associated with a first entity type associatedwith a first category of data associated with the merchant system,wherein the first entity type comprises a first data field storing afirst data value corresponding to the first category and the merchantsystem; receive a second selection from the merchant system of a secondinput field, wherein the second input field is associated with a secondentity type associated with a second category of data associated withthe merchant system, wherein the second entity type comprises a seconddata field storing a second data value corresponding to the secondcategory and the merchant system; generate a search experience interfacecomprising the first input field and the second input field; display thesearch experience interface to an end user system; receive, from the enduser system, a first search term provided via the first input field ofthe search experience interface; receive, from the end user system, asecond search term provided via the second input field of the searchexperience interface; and execute a search of a set of data comprisingthe first entity type and the second entity type associated with themerchant system in view of the first search term and the second searchterm.
 8. The system of claim 7, the processing device to execute theinstructions to: associate the first input field with a first set ofparameters; and display the first set of parameters in connection withthe first input field in the search experience interface.
 9. The systemof claim 8, wherein the first search term corresponds to a firstparameter of the first set of parameters.
 10. The system of claim 7,wherein execution of the search comprises accessing the first data fieldof the first entity type and the second data field of the second entitytype.
 11. The system of claim 7, wherein the first entity type is acustom entity type generated in response to one or more inputs receivedfrom the merchant system.
 12. The system of claim 7, the processingdevice to execute the instructions to: receive an update to the firstdata of the first entity type; in response to receiving the update tothe first data, generating an updated first entity type; and distributethe updated first entity type to a plurality of business listingprovider systems configured to provide search results associated withthe merchant system in response to a search query from an end usersystem, wherein the search results comprise the update to the firstdata.
 13. The system of claim 7, the processing device to execute theinstructions to: generate a relationship type between the first entitytype and the second entity type, wherein the relationship typerepresents a relationship between the first entity type and the secondentity type.
 14. The system of claim 7, wherein the search is executedin response to receipt of a single indication of a search action fromthe merchant system.
 15. A non-transitory computer readable storagemedium having instructions that, if executed by a processing device,cause the processing device to: receive a first selection from amerchant system of a first input field, wherein the first input field isassociated with a first entity type associated with a first category ofdata associated with the merchant system, wherein the first entity typecomprises a first data field storing a first data value corresponding tothe first category and the merchant system; receive a second selectionfrom the merchant system of a second input field wherein the secondinput field is associated with a second entity type associated with asecond category of data associated with the merchant system, wherein thesecond entity type comprises a second data field storing a second datavalue corresponding to the second category and the merchant system;generate a search experience interface comprising the first input fieldand the second input field; display the search experience interface toan end user system; receive, from the end user system, a first searchterm provided via the first input field of the search experienceinterface; receive, from the end user system, a second search termprovided via the second input field of the search experience interface;and execute a search of a set of data comprising the first entity typeand the second entity type associated with the merchant system in viewof the first search term and the second search term.
 16. Thenon-transitory computer readable storage medium of claim 15, theprocessing device to: associate the first input field with a first setof parameters; and display the first set of parameters in connectionwith the first input field in the search experience interface, whereinthe first search term corresponds to the first set of parameters. 17.The non-transitory computer readable storage medium of claim 15, theprocessing device to: generate, in view of the first search term, anotification comprising a recommendation relating to the set of data;provide the notification to the merchant system; in response to thenotification, receive additional data from the merchant system toinclude in the set of data; and generate, based on the additional data,an entity type associated with the merchant system.
 18. Thenon-transitory computer readable storage medium of claim 15, theprocessing device to: generate a set of search results in response tothe search based on the first search term and the second search term;and display the set of search results to the end user system.